Identification Of Causes Of Varation In The Semiconductor Manufacturing Processes By Statistical Analysis A Six Sigma Approach.

i

IDENTIFICATION OF CAUSES OF VARATION IN THE SEMICONDUCTOR MANUFACTURING PROCESSES BY STATISTICAL ANALYSIS : A SIX SIGMA

APPROACH

GUNASEGARAN A/L VIJAYA KUMARAN

This report is submitted in particular fulfilment of the requirements for the award of Bachelor of Electronic Engineering (Industial Engineering) With Honours

Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia Melaka

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UNIVERSTI TEKNIKAL MALAYSIA MELAKA

FAKULTI KEJURUTERAAN ELEKTRONIK DAN KEJURUTERAAN KOMPUTER BORANG PENGESAHAN STATUS LAPORAN

PROJEK SARJANA MUDA II

Tajuk Projek :

IDENTIFICATION OF CAUSES OF VARATION IN THE SEMICONDUCTOR MANUFACTURING PROCESSES BY STATISTICAL ANALYSIS : A SIX SIGMA APPROACH Sesi

Pengajian : 2009/2010

Saya GUNASEGARAN A/L VIJAYA KUMARAN

mengaku membenarkan Laporan Projek Sarjana Muda ini disimpan di Perpustakaan dengan syarat-syarat kegunaan seperti berikut:

1. Laporan adalah hakmilik Universiti Teknikal Malaysia Melaka.

2. Perpustakaan dibenarkan membuat salinan untuk tujuan pengajian sahaja.

3. Perpustakaan dibenarkan membuat salinan laporan ini sebagai bahan pertukaran antara institusi pengajian tinggi.

4. Sila tandakan ( √ ) :

SULIT*

(Mengandungi maklumat yang berdarjah keselamatan atau kepentingan Malaysia seperti yang termaktub di dalam AKTA RAHSIA RASMI 1972)

TERHAD*

(Mengandungi maklumat terhad yang telah ditentukan oleh organisasi/badan di mana penyelidikan dijalankan)

TIDAK TERHAD

Disahkan oleh:

__________________________ ___________________________________

(TANDATANGAN PENULIS) (COP DAN TANDATANGAN PENYELIA)

Alamat Tetap: 37, Tasek Mutiara7, Taman Tasek Mutiara, 31400, Ipoh, Perak.

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“I declare that this project report is the result of my own research except for quotes as cited in the references.”

Signature : ………..

Name : GUNASEGARAN A/L VIJAYA KUMARAN

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“I hereby declare that I have read this project report and in my opinion this project report is sufficient in terms of scope and quality for the award of Bachelor of Electronic

Engineering (Industrial Engineering) With Honours.”

Signature : ………

Name of Supervisor : Miss. FARAH SHAHNAZ FEROZ

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Specially.. To my beloved parents To my kind brothers and sisters And not forgetting to all friends

For their

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ACKNOWLEDGEMENTS

I have just completed my Final Year Project (PSM) and thesis in sufficient time. First of all, I would like to take this opportunity to express my appreciation to some organizations and individuals who have kindly contributed for my final year project in UTeM. With the Cooperation and contribution from all parties, the objectives of the project; soft skills, knowledge and experience were gained accordingly even this is just part of the whole project. Furthermore, I would like thank to me supervisor. Miss. Farah Shahnaz Feroz for the proper guidance, cooperation and involvement throughout my Final Year Project. Her effort to ensure the successful and comfort ability of student under her responsibility was simply not doubtful. Moreover, I would like to extend my sincere acknowledgement to my parents and family members who have been very supportive for the past six months. Their understandings and support in term of moral financial were entirely significance towards the project completion. Last but not list, my appreciation goes to my fellow students in UTeM, especially for who are from KEKK. Their willingness to help, opinions and suggestions on some matters, advices and technical knowledge are simply precious while doing upon completion of my final year project.

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ABSTRACT

Six Sigma is an improvement process, developed by Motorola in 1985 that continually strives for perfection by reducing variation in the production processes. In semiconductor industry, the output of production is important. Increasing the output without maintaining the quality would lead to increase in variation in the process. By reducing this variation, it will improve the quality of the product. The objective of this project is to detect and find possible ways to reduce the variation in semiconductor manufacturing production of IC (Integrated Circuit). Production data from the industry will be analyzed to detect data variation. From here, a possible solution will be proposed to the industry. Causes of variation can be classified as common and special causes. In this case, special causes of variation are taken as subject to do the analysis. Wrong ingredient, wrong process setting, or an untrained operator is example of special causes. To observe and analysis the variations of the data, the Process Capability (Cp) method is use. Process capability is a method by compress the output of an in-control process to the specification limits by using capability indices. The target to achieve in this analysis is to detect and find possible ways to reduce the special cause’s variation in manufacturing of IC (Integrated Circuit). All products and services are a result of some process. Also, Six Sigma benefits others beside customers. Six Sigma not only treats manufacturing as parts of a large system, it removes the narrow, inward focus of the traditional approach. A thorough literature study on Six Sigma, Statistical Process Control tools and the implementation of Six Sigma in the semiconductor industry will be performed.

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ABSTRAK

Laporan ini adalah laporan disediakan untuk Projek Sarjana Muda, kanduanan laporan ini termasuk rekacipta dan pembangunan untuk sistem penempahan gudang. Projek ini adalah seperti apa yang ingin disampaikan melalui tajuk di atas, iaitu projek ini menitikberatkan proses semasa penembahan produk dalam gudang dan juga penghantaran produk dari gudang. Jadi sistem ini juga akan implikasi sistem pengurusan gudang. Projek ini adalah direka dengan Visual Studio 2008 bergabung dengan pangkalan data yang direka dengan Microsoft Access 2007, manakala perkakasan projek ini, sistem ini boleh mengawal motor melalui mikropengawal, iaitu Microchip PIC 16f877A. Komunicasi perisian dengan perkakasan projek ini adalah melalui modul Universal Asynchronous Receiver Transmitter (UART). Komunicasi adalah dupleks penuh, ini merujukkan komunikasi ini adalah dua hala. Satu Universal-Serial-Bus-to-Serial-Port penukar yang menyepadukan dengan RS-232 digunakan untuk sambungan ini. Sistem ini juga membolehkan pengguna untuk menguruskan dalam process penembahan, pembayaran, gudang kawalan, penghantaran produk, laporan kerosakan, penukaran kerosakan, dan akhirnya pengawalan inventori. Pelbagai process yang disebuti adalah digabung menjadi sebuah sistem dan perkakasan ini diguna sebagai pengawal untuk mengawal tali pengakut untuk mengakut barang-barang dari gudang kepada stesen penghantaran. Perkakasn ini dikawal semasa penghantaran produk dan laporan kerosakan produk dalan sistem. Ia dikawal melalui sistem untuk diaktif dengan sistem bagi isyarat untuk membenarkan 2 motor berjalan dengan dua hala yang berlainan, satu untuk masuk dan pengeluaran produk. Untuk penembahan sistem ini, data-data akan disimpan dalam pangkalan data untuk menyenangkan pengurusan proses penembahan. Jaringan pangkalan data dengan sistem adalah disambung dengan modul

ix ActiveX Database Objects. Pangkalan data direka dengan gabungan data yang dikumpul. Sistem ini boleh diaplikasikan di gudang industri, dan juga kedai kedai untuk menaikkan kadar kecekapan penembahan yang sedia ada kini dan mengurangkan kekurangan yang hadapi.

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TABLE OF CONTENT

CHAPTER TITLE PAGE

PROJECT TITLE i

CONFIRMATION REPORT STATUS ii

DECLARATION iii

SUPERVISOR CONFIRMATION iv

DEDICATION v

ACKNOWLEDGEMENT vi

ABSTRACT vii

ABSTRAK viii

TABLE OF CONTENT x

LIST OF TABLE xiv

LIST OF FIGURE xv

LIST OF ABBREVIATION xvii

LIST OF APPENDIX xviii

xi

1.1 Project background 2

1.2 Objective 3

1.3 Problem statement 4

1.4 Scope 4

1.5 Methodology project 5

1.6 Outline of PSM report 6

II LITERATURE REVIEW 8

2.1 Literature review overview 8

2.2 Comparison six sigma with three sigma and other sigma level

8

2.3 Quality test for wire bonding 10

2.3.1 Wire Pull Tes 12

2.3.2 Ball shear testing 14

2.4 Six Sigma in other services 14

2.5 Statistical process control (SPC) 16

2.6 Control chart 18

2.7 Variation 20

2.7.1 Common cause variation 20 2.7.2 Special cause variation 21 2.8 Formula in calculating the grand means, ,

xii Standard deviation, σ_{, Control Limit of control} chart, (UCL and LCL) 22

2.9 Process Capability 23

2.9.1 Capability and Performance Indices 24

2.9.2 Formula to calculate the Cp, Cpk , Pp, Ppk. 25 2.10 Process Capability pattern recognition 28

III METHODOLOGY 30

3.1 Methodology Overview 30

3.2 Six sigma strategy 31

3.3 Produce the variables chart for subgroup via

Control Chart 33

3.4 Produce the variables chart for individual via

Control Chart 36

3.5 Produce the Probability Plot graph 36 3.6 Producing the process capability graph 38

IV RESULT AND DISCUSSION 40

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4.2 Case 1:External test of IC 40

4.3 Discussion the result of external test IC 46

4.4 Case 2:Internal test IC 48

4.4.1Wire pull test 48

4.2-Ball shear test 49

4.3-Ball thickness consistency 50

4.4.4-Loop height consistency 51

4.4.5-Ball placement consistency 52 4.5 Discussion of the result of external IC test 63

V CONCLUSION AND RECOMMENDATION 66

5.1 Conclusion 66

5.2 Recommendation 67

VI REFERENCE 69

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LIST OF TABLE

NO TITLE PAGE

2.1 DPMO at sigma levels 9

2.2 Six Sigma in service organizations 15

2.3 CSFs, CTQs, KPIs AND TOOLS ACROSS SERVICE ORGANIZATIONS

16

2.4 The relationship Cp, Cpk, Pp, Ppk 25

2.5 The Cp and Cpk in Process Centred and Process off-centre by 1.5σ

27

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LIST OF FIGURE

NO TITLE PAGE

1.1 Industry production theories 3

1.2 Project flowchart 6

2.11 Ball bond shape (Note the size of the ball) 11 2.12 Typical gold bond wire loop from the chip to the

leadframe

11

2.13 Bond pull test 12

2.14 Ball lift and wedge (weld) lift failure 12

2.15 Pull test failure modes 13

2.16 Neck break, Midspan break and Heel break 13

2.17 Weld lift 13

2.18 Ball shear test 14

2.19 Control chart patterns 19

2.20 Common cause of variations 21

2.21 Special causes of variations 22

2.22 Process output within specification limits 28 3.1 Flowchart of Methodology and overall of the process 30

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3.2 Relationship DMADD, DMAIC, DMADV 31

3.3 DMAIC flow chart 32

4.1 Structure of an IC product 40

4.2 Xbar-R Chart for standoff 44

4.3 Xbar-S Chart for standoff 44

4.4 Pb plot for standoff 45

4.5 Xbar-R Chart for spacing 45

4.6 Xbar-S Chart for spacing 46

4.7 Pb plot for spacing 46

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LIST OF ABBREVIATION

DPMO - defects per million opportunities

IC - Integrated Circuit

Cp - Process Capability

PSM - Projek Sarjana Muda

SPC - Statistical Process Control

DFSS - Design for Six Sigma

DMAIC - define, measure, analyze, improve, and control

USL - Upper Specification Limit

LSL - Lower Specification Limit

UCL - Upper Control Limit

LCL - Lower Control Limit

Cpk - Critical Process index

Pp - Process Performance

Ppk - Process Performance Index

xviii

LIST OF APPENDIX

NO TITLE PAGE

1

CHAPTER 1

INTRODUCTION

There is a letter in Greek, σ _{which is called as sigma used by statisticians to} represent the standard deviation for a set of data [16]. The standard deviation is a value which indicated that the total number of individual data deviated from the mean value. This means that an estimation value of the variation in a set of data measurement is provides by the standard deviation. Currently, the sigma levels from one to six have been applied in different industries all over the world. However, the six sigma level is the best used in several manufacturing and non-manufacturing industry which is confirmed by Motorola. Six sigma is a quality-focused program that utilizes worker teams to accomplish projects aimed at improving an organization’s operational performance. The Six Sigma has a vision in term of quality which equates with only 3.4 defects per million opportunities for each product or service transaction and it strives for perfection. Achieving the six-sigma quality can ensure both dependable quality and production efficiency. Its application not only to the production of goods and services, but it also concern about technical processes as well. In addition, it is capable to confront the highly competitive challenges and the variable changes of environment. Other than the application of Six Sigma in manufacturing and non-manufacturing industry, it has also implemented in several organization such as health care and financial service. Moreover,

2 its application is gradually following up in other services such as call centers, utilities and publicservices.

1.1-Project background

The Six Sigma concept was first established in the 1980s by Motorola [20]. Motorola has generated the idea which was related to the discussion of quality from measurement of quality level in hundred change into a discussion of parts-per-million or even parts-per-billion. Based on the idea from Motorola, the old ideas about "acceptable quality levels" could no longer be tolerated as the modern technology become more complex. Hence, the perfect quality level was required in modern business.

A good quality services can cause the growth of economies which influence the increase of important services for the developed and developing nations. Therefore, interest in applying the Six Sigma concept is growing in manufacturing and services. Traditionally, the application of Six Sigma was not implemented in majority of manufacturing organization. With the implementation of Six Sigma, many service organizations have improving in terms of success rate and customer satisfaction. Most of the service organizations are Citibank, Bank of America, American Express, Caterpillar and Baxter Healthcare in US and Europe [6],[7],[8],[9],[15].

In any manufacturing semiconductor industry, the number of quality output of the production is important. With the increase of the output regardless on maintaining the quality would cause the increase in variation in the process. The way of reducing variations in the process is by maintaining the quality of products.

3

Figure 1.1:Industry production theories

The main objective of this project is to identify and find a possible solution to reduce the variation in semiconductor manufacturing production of IC (Integrated Circuit). Once the variation has identified, the problem can be solved effectively.

1.2-Objective

The objective in this project is:

1. To study and explain the benefits of the implementation of Six Sigma in the semiconductor industry to gain competitive advantage.

2. To identify production problems related to shifts and variations through control charts and Process Capability Index (Cp) analyses.

3. To identify possible solutions in reducing the defective IC in a semiconductor industry.

4. To propose a method using the Six Sigma approach to reduce variation in the production process.

5. To suggest possible ways in improving business performance and process management in semiconductor industry.

Output Production

Process Variation

4

1.3-Problem statement

Today, most of the highly innovative semiconductor industry companies such as Motorola, Toshiba and Agilent Tech have to proceed with high volume production before their process achieve to maturity. The high volume of production is for the company to maintain their reputation and compete with other semiconductor industry. Beside that, the customer product also must have good quality. Therefore, most of the well known companies faced with the problem of high variation in a process when the yielding of output product is increased. Due to this problem, quality of product will also decrease. When product quality is not within the customer specification, other process will affect simultaneously. An increase in variation will cause the increment of expansion in production cost. In addition, time spent for rework for defect products lead a lot of problem and chaos in the production line. This entire problem is required to be overcome to maintain the reputations of the company.

1.4-Scope

In this project, there are three assumptions are made from the data collected:

• Independence of the data.

• Normal-Gaussian distribution also called the Gaussian distribution is an

important family of continuous probability distributions, applicable in many fields. Each member of the family may be defined by two parameters, location and scale: the mean ("average", ) and variance (standard deviation squared) σ2, respectively.

• The data is randomly distributed.

In this project, it has two limitation levels that cannot to avoid. Firstly, to get the zero-defects of the variation of producing an IC. This is because every process has its variation. From here, possible ways to reduce process variation will be studied.

5 Secondly, data collection is confidential and it is handled by the company staff. I have no contact when the data is collected and how data collection is handled. Human error that occurs when taking the data also affects the analysis.

To analyze the data, Six Sigma method used with the help of Statistical Software such as MINTAB 14.

1.5 -Methodology project

I will also perform a thorough literature study and review on Six Sigma, Statistical Process Control tools, and the implementation of Six Sigma, Statistical Process Control tools, and the implementation of Six Sigma in the semiconductor industry. The technique of statistical process control, control charts and Process Capability Index (Cp) can be used to identify productions problems related to shifts and variation. The flow chart have shown in below is related to my procedure to implement this project

6

Figure 1.2: Project flowchart

In this project, I propose a method using Six Sigma approach to reduce variation in the production process. This would thus eliminate rework and customer callbacks caused by defects, leading to lower production costs and improve customer’s satisfaction.

1.6-Outline of PSM report

This PSM report consists of five chapters. The first chapter discusses the background, objectives, problem statement, scope and methodology of this project. Chapter two discusses the theory of Six Sigma and includes the literature reviews that have been done. In addition, it also discusses the process flow of producing an IC and

Start

Literature review

Get data

Analysis

Detect data variation

Look for variation causes

Propose a solution

CHAPTER 1

INTRODUCTION

There is a letter in Greek, σ _{which is called as sigma used by statisticians to} represent the standard deviation for a set of data [16]. The standard deviation is a value which indicated that the total number of individual data deviated from the mean value. This means that an estimation value of the variation in a set of data measurement is provides by the standard deviation. Currently, the sigma levels from one to six have been applied in different industries all over the world. However, the six sigma level is the best used in several manufacturing and non-manufacturing industry which is confirmed by Motorola. Six sigma is a quality-focused program that utilizes worker teams to accomplish projects aimed at improving an organization’s operational performance. The Six Sigma has a vision in term of quality which equates with only 3.4 defects per million opportunities for each product or service transaction and it strives for perfection. Achieving the six-sigma quality can ensure both dependable quality and production efficiency. Its application not only to the production of goods and services, but it also concern about technical processes as well. In addition, it is capable to confront the highly competitive challenges and the variable changes of environment. Other than the application of Six Sigma in manufacturing and non-manufacturing industry, it has also implemented in several organization such as health care and financial service. Moreover,

its application is gradually following up in other services such as call centers, utilities and public services.

1.1-Project background

The Six Sigma concept was first established in the 1980s by Motorola [20]. Motorola has generated the idea which was related to the discussion of quality from measurement of quality level in hundred change into a discussion of parts-per-million or even parts-per-billion. Based on the idea from Motorola, the old ideas about "acceptable quality levels" could no longer be tolerated as the modern technology become more complex. Hence, the perfect quality level was required in modern business.

A good quality services can cause the growth of economies which influence the increase of important services for the developed and developing nations. Therefore, interest in applying the Six Sigma concept is growing in manufacturing and services. Traditionally, the application of Six Sigma was not implemented in majority of manufacturing organization. With the implementation of Six Sigma, many service organizations have improving in terms of success rate and customer satisfaction. Most of the service organizations are Citibank, Bank of America, American Express, Caterpillar and Baxter Healthcare in US and Europe [6],[7],[8],[9],[15].

In any manufacturing semiconductor industry, the number of quality output of the production is important. With the increase of the output regardless on maintaining the quality would cause the increase in variation in the process. The way of reducing variations in the process is by maintaining the quality of products.

Figure 1.1:Industry production theories

The main objective of this project is to identify and find a possible solution to reduce the variation in semiconductor manufacturing production of IC (Integrated Circuit). Once the variation has identified, the problem can be solved effectively.

1.2-Objective

The objective in this project is:

1. To study and explain the benefits of the implementation of Six Sigma in the semiconductor industry to gain competitive advantage.

2. To identify production problems related to shifts and variations through control charts and Process Capability Index (Cp) analyses.

3. To identify possible solutions in reducing the defective IC in a semiconductor industry.

4. To propose a method using the Six Sigma approach to reduce variation in the production process.

5. To suggest possible ways in improving business performance and process management in semiconductor industry.

Output Production

Process Variation

1.3-Problem statement

Today, most of the highly innovative semiconductor industry companies such as Motorola, Toshiba and Agilent Tech have to proceed with high volume production before their process achieve to maturity. The high volume of production is for the company to maintain their reputation and compete with other semiconductor industry. Beside that, the customer product also must have good quality. Therefore, most of the well known companies faced with the problem of high variation in a process when the yielding of output product is increased. Due to this problem, quality of product will also decrease. When product quality is not within the customer specification, other process will affect simultaneously. An increase in variation will cause the increment of expansion in production cost. In addition, time spent for rework for defect products lead a lot of problem and chaos in the production line. This entire problem is required to be overcome to maintain the reputations of the company.

1.4-Scope

In this project, there are three assumptions are made from the data collected:

• Independence of the data.

• Normal-Gaussian distribution also called the Gaussian distribution is an important family of continuous probability distributions, applicable in many fields. Each member of the family may be defined by two parameters, location and scale: the mean ("average", ) and variance (standard deviation squared) σ2, respectively.

• The data is randomly distributed.

In this project, it has two limitation levels that cannot to avoid. Firstly, to get the zero-defects of the variation of producing an IC. This is because every process has its variation. From here, possible ways to reduce process variation will be studied.

Secondly, data collection is confidential and it is handled by the company staff. I have no contact when the data is collected and how data collection is handled. Human error that occurs when taking the data also affects the analysis.

To analyze the data, Six Sigma method used with the help of Statistical Software such as MINTAB 14.

1.5 -Methodology project

I will also perform a thorough literature study and review on Six Sigma, Statistical Process Control tools, and the implementation of Six Sigma, Statistical Process Control tools, and the implementation of Six Sigma in the semiconductor industry. The technique of statistical process control, control charts and Process Capability Index (Cp) can be used to identify productions problems related to shifts and variation. The flow chart have shown in below is related to my procedure to implement this project

Figure 1.2: Project flowchart

In this project, I propose a method using Six Sigma approach to reduce variation in the production process. This would thus eliminate rework and customer callbacks caused by defects, leading to lower production costs and improve customer’s satisfaction.

1.6-Outline of PSM report

This PSM report consists of five chapters. The first chapter discusses the background, objectives, problem statement, scope and methodology of this project. Chapter two discusses the theory of Six Sigma and includes the literature reviews that have been done. In addition, it also discusses the process flow of producing an IC and

Start

Literature review

Get data

Analysis

Detect data variation

Look for variation causes

Propose a solution